Pilot Study of Integration of Wildlife Impact Analysis into Spatial Environmental Assessment Tool for Marine Hydrokinetic Energy

摘要

This study aimed to produce a pilot spatial model, building upon the existing quantitative Spatial Environmental Assessment Tool (SEAT), to evaluate risks associated with marine hydrokinetic energy (MHK) development within the Pacific Marine Energy Center South Energy Test Site, located off Newport, Oregon. The goal is to establish an approach for integrating natural resource sensitivities with changes in physical conditions caused by wave energy converter arrays to inform planning and impact assessment. To generate the model inputs, a benthic substrate proxy within the project area was defined as a "sensitive resource" input (Receptor), using the Risk (Rτ) output points from the SEAT model to identify areas that could be impacted by the operation of a MHK device (Threshold). Risks were further investigated by overlaying federally designated Habitat of Potential Concern, Essential Fish Habitat, and critical habitat to identify sensitive benthic resources (Secondary Constraint) within the project area. The last iteration of the model focused on using nearshore habitats for threatened coho salmon (Oncorhynchus kisutch) outmigrating from rivers to demonstrate how a higher taxon could be incorporated into the pilot model by assigning risk based on proximity to the shoreline. This approach allows the analyst to weight the sensitivity of natural resources and place secondary constraints and ocean conditions into the assessment for an integrated picture and can accommodate multiple taxa, seasons, habitats, and locations. Overall, the results of the four models were dependent on the weighting and scale of the data. The outcomes of this study are meant to demonstrate ability to integrate models and are not based on particularly defensible criteria. More rigorous literature review and risk assessment process would be necessary to demonstrate the project specific risk of impacts from MHK devices. This type of modeling can inform resource management and planning, and ultimately assist in identifying priority impact issues and mitigation needs throughout project siting and development, which will reduce risk and cost to developers.